Will Near-Zero Pricing Happen with Medical and Legal Advice?

Legendary venture capitalist Vinod Khosla predicts free medical and legal advice in about a decade, because of artificial intelligence. Some will dismiss the prediction as fanciful, given many similar predictions in the past. 

As outlandish as that might appear, it is a common belief or prediction in the digital era, though there were some predictions that electricity, for example, would be “free” in the older analog world. 

There were inaccurate predictions that nuclear power, for example, would be so cheap it would not be worth metering its use. 

Study Title/Publication	Prediction	Date of Prediction	Publisher	Reason for Inaccuracy
"The Promise of Nuclear Power" by Lewis Strauss, Chairman of the U.S. Atomic Energy Commission	Predicts that nuclear power will become so cheap that it will be "too cheap to meter."	1954	U.S. Atomic Energy Commission	Underestimated the costs of constructing and maintaining nuclear power plants, as well as the risks associated with nuclear accidents.
"Nuclear Power: The Answer to the Energy Crisis" by Alvin Weinberg, Director of the Oak Ridge National Laboratory	Predicts that nuclear power will make electricity "too cheap to meter" by 1969.	1960	Public Affairs Press	Overestimated the rate at which nuclear power plants would be built and underestimated the costs of building and operating them.
"Nuclear Energy and the Future of Power" by David Lilienthal, former Chairman of the U.S. Atomic Energy Commission	Predicts that nuclear power will provide "a virtually inexhaustible supply" of electricity at "extremely low cost."	1967	Basic Books	Underestimated the environmental and safety concerns associated with nuclear power.

In recent decades, predictions of dramatically-lower product pricing--essentially free or near zero--have been made in a variety of areas where digital technology was expected to operate. In virtually all cases, assumptions were made about substitute products that would operate so affordably that existing products would not be attractive. 

Study Title/Publication	Prediction	Date of Prediction	Publisher	Reason for Inaccuracy
"The World Without Cars" by Peter Newman and Jeff Kenworthy	Predicts that cars will become obsolete in cities by 2030.	1989	Pluto Press	Underestimated the continued popularity of cars and the challenges of transitioning to car-free cities.
"The Information Economy: How Digital Networks Will Transform the World" by Manuel Castells	Predicts that the information economy will lead to a more equitable society.	1996	Blackwell Publishers	Overestimated the potential of the information economy to reduce inequality.
"The Long Tail: Why the Future of Business Is Selling Less of More" by Chris Anderson	Predicts that the internet will allow niche products to become more profitable than mass-market products.	2006	Hyperion	Underestimated the power of marketing and branding in the digital age.
"The Second Machine Age: Work, Progress, and the Future of Mankind" by Erik Brynjolfsson and Andrew McAfee	Predicts that automation will lead to widespread unemployment.	2011	W. W. Norton & Company	Overestimated the speed at which automation will replace human workers.
"The Rise of the Robots: Automation and the Future of Work" by Martin Ford	Predicts that robots will eventually replace most human workers.	2015	Basic Books	Overestimated the capabilities of robots and underestimated the adaptability of human labor.

All that noted, predictions about near-zero pricing for any variety of products continue to be made. It might be too soon to know whether such predictions will prove incorrect. And relative abundance, in some instances, might have outcomes largely indistinguishable from predictions of absolute abundance. 

Internet access is not “free,” for example, but its price is low enough that usage is not a barrier. Many other products, such as search, shopping, social media and some forms of content cost so little that consumption can be subsidized fairly easy by advertising or low usage fees. 

Study/Story	Prediction	Date of Prediction	Publisher
"The Age of Free: Why We'll Soon Pay Nothing for Most of What We Use"	"Within the next two decades, many of the things we now pay for—electricity, food, transportation, housing, healthcare—will become essentially free."	2014	Jeremy Rifkin
"The Free Economy: When Everything's Free"	"In the future, we will be able to produce goods and services in great abundance at very low cost, or even for free."	2016	Tom Slee
"The Future of Abundance: How the Products of Human Ingenuity Will Make the World a Better Place"	"The abundance created by technology will eventually lead to a world where everyone has access to the basic necessities of life."	2019	Peter Diamandis and Steven Kotler
"Radical Abundance: How to Create a World of More Than Enough"	"The potential for abundance exists in every sector of the economy."	2020	Marianne Williamson
"The World We Made: How Our Future Will Be Shaped by Technology - For Better or for Worse"	"We are on the cusp of a new era of abundance, in which the cost of producing goods and services will continue to decline, and the potential for human flourishing will expand."	2021	Michael J. Sandel
"The Future of Electricity: Scenarios and Forecasts to 2040" by the International Energy Agency (IEA)	Electricity prices will fall significantly in the coming decades, with the average price in industrialized countries expected to be about 50% lower in 2040 than in 2018.	2019	IEA
"The Free Economy" by Jeremy Rifkin	The marginal cost of producing and delivering many goods and services, including electricity, information, and transportation, is approaching zero. This will lead to a new era of economic prosperity in which many products and services will be essentially free to consumers.	2014	Jeremy Rifkin
"The Zero Marginal Cost Society" by Thomas Philippon	The marginal cost of producing and delivering many goods and services, including electricity, information, and transportation, is approaching zero. This will lead to a new era of economic inequality in which a small number of companies will control the vast majority of wealth.	2019	Thomas Philippon
"The Rise of the Sharing Economy" by Rachel Botsman	The rise of digital technologies is making it easier for people to share goods and services, such as cars, homes, and clothes. This will lead to a new era of economic prosperity in which many products and services will be essentially free to consumers.	2013	Rachel Botsman
"The Age of Disruption" by Geoffrey G. Parker	The rise of digital technologies is disrupting many industries, including the energy, telecommunications, and transportation industries. This will lead to a new era of economic uncertainty in which many companies will struggle to survive.	2014	Geoffrey G. Parker
"The Economics of Energy" by Jeremy Rifkin	Predicts that solar power will become so abundant and inexpensive that it will be essentially free for consumers.	2014	Jeremy Rifkin
"The Future of Work" by Martin Ford	Predicts that automation will eventually make many jobs obsolete, leading to a situation where governments provide a universal basic income to all citizens.	2016	Basic Books
"The Age of Surveillance Capitalism" by Shoshana Zuboff	Predicts that data will become the most valuable resource in the world, and that companies will be able to extract immense profits from it by selling it to advertisers and other third parties.	2019	PublicAffairs
"The Next Revolution: Work, Wealth, and the Future of Capitalism" by Nathan Myhrvold	Predicts that artificial intelligence will eventually surpass human intelligence, leading to a new era of unprecedented economic prosperity.	2022	Crown Business
"The 21st Century Revolution: A New Economic Vision" by Jeremy Rifkin	Predicts that a third industrial revolution, based on renewable energy and distributed manufacturing, will eventually replace the fossil fuel-based industrial economy.	2021	St. Martin's Press

But sometimes, intangible products and digital products do approach near-zero pricing levels, reducing barriers to usage. And that is the reason some believe AI is going to attack price levels for any number of intangible products including advice and diagnosis. 

Near-zero pricing might seem outlandish, but not for intangible products. We already have seen that impact in content delivery, shopping and information discovery, as well as social media. And advice based on experience might be the next large set of areas to be affected by the near-zero pricing trend.

How Will AI Reshape Data Centers?

Among the predictions about the impact of artificial intelligence on data centers are a few salient statistics. Sanjay Bhutani, AdaniConneX chief business officer, notes that AI will drive data centers from 54 gigawatts  to perhaps 90 Gwatts. 

Likewise, Gautham Gnanajothi, Frost and Sullivan global VP estimates data center investment will grow from about $300 billion to $775 billion over the next 10 years, of which the largest-eight hyperscalers currently represent about $110 billion in annual investment out of the total of $300 billion globally. 

Capex estimates vary from firm to firm, depending on assumptions about growth rates. Generally speaking, earlier studies show lower expected capex in 2033, compared to more-recent studies that include assumptions about additional requirements to support AI. 

Publisher	Prediction	Date
Frost & Sullivan	$610 billion	2023-10-04
IDC	$570 billion	2023-09-27
Gartner	$530 billion	2023-08-15
MarketsandMarkets	$590 billion	2023-07-12
Mordor Intelligence	$630 billion	2023-06-08
Grand View Research	$550 billion	2023-05-03
Technavio	$510 billion	2023-04-19
Fortune Business Insights	$560 billion	2023-03-07
Allied Market Research	$540 billion	2023-02-14
Statista	$580 billion	2023-01-10

Study Title	Capital Investment Prediction (2033)	Date of Publication	Publisher
Global Data Center Market Size, Trends, and Forecasts, 2022-2030	$814 billion	September 2023	Fortune Business Insights
Data Center Market Size, Share, Trends & Growth, 2023-2032	$795.2 billion	October 2023	Grand View Research
Data Center Market Global Report 2023	$768.7 billion	November 2023	Market Research Future
Data Center Market Size, Share & Trends Analysis Report by Component (IT Infrastructure, Facility Infrastructure), by Deployment Type (On-Premises, Cloud), by Vertical (BFSI, IT & Telecom, Retail, Healthcare), Forecast, 2023 - 2028	$742.5 billion	November 2023	Allied Market Research
Data Center Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2023 - 2028	$721.4 billion	November 2023	Global Market Insights
Future of Data Centers: 2023-2033	$698.2 billion	October 2023	Data Center Frontier
Data Center Market Global Trends and Forecast to 2030	$675.1 billion	September 2023	IDC
The Future of Data Centers in the Post-Pandemic Era	$652.0 billion	August 2023	Gartner
Data Center Market Size and Growth Analysis, 2023-2030	$631.9 billion	July 2023	ReportLinker
Global Data Center Industry Outlook 2023	$610.8 billion	June 2023	Frost & Sullivan

If the same ratios hold in a decade, hyperscalers will be investing about $284 billion, while other data centers invest about $496 billion, using the Frost and Sullivan estimate made by Gnanajothi. 

On the other hand, not all of the AI impact will necessarily involve “more” commitment of resources. Since AI model training does not require the same level of redundancy as do other operations, it is possible that AI training will represent less resource intensity than other types of operations, Gnanajothi suggests. 

Also, the denser footprint AI represents might also mean less proportional demand for land and building space, compared to existing operations. 

Also, AI training operations might not always be so latency dependent, though inference operations might often require edge computing, says Phillip Marangella, EdgeConnex chief marketing officer. 

And data centers, just like any other enterprise or organization, should be able to use AI to improve the efficiency of its operations. In fact, says Bhutani, AdaniConnex already uses AI to improve safety operations when it is building or operating a facility. 

AI Leaders and Laggards?

There are lots of head fakes in technology. At least temporarily, virtual reality, augmented reality, automated vehicles, three-dimensional television, smart glasses, virtual assistants and wearable technology have failed to make much of an impact. 

User-generated content has succeeded as the underpinning of sustainable business models, but not as it was originally envisioned, as a substitute for professionally-produced content. 

On the other hand, Netscape made the multimedia World Wide Web accessible, while the Web made the internet a “must have” experience.  Facebook created social media. Google search changed the way people learn and find things. The iPhone changed personal devices. Twitter changed the way newsmakers get their news. Netflix and YouTube changed the way people consume video content. 

ChatGPT and generative AI seemingly have nearly-instantly shifted and changed the computing function and the application of computing to apps, devices and platforms. 

But it is worth pointing out that we are early in a shift to an AI-driven future. A few of you might recall the early days of personal computing or the internet and what it was capable of in 1995. The point is that we are quite likely to be surprised with the outcomes.

Today’s apparent “leaders” might not be in existence in a decade, much less continue to lead. Laggards and upstarts might overtake today’s leaders in markets as they exist in a decade or two. 

How AI will reshape apps, platforms, devices and experiences is fluid and unsettled. So most of our predictions will prove false, in part, or in whole. 

In 1995, the idea of “ad-supported technology firms” might have seemed silly. But now we have witnessed the dominance of firms such as Google and Meta, which are nothing if not ad-supported developers of technology products. 

The emergence of online commerce was easier to predict. But few in 1995 believed video streaming services could not only compete with, but supplant, linear video. 

So “nobody saw this coming” is still likely to be among the outcomes of AI, a decade or two in the future, especially if AI turns out to be a general-purpose technology like electricity. 

General-purpose technologies are fundamental innovations which have a broad range of applications and can be used to improve productivity in a variety of industries. They are often characterized by their ability to be adapted to new uses and to generate new industries, increase productivity and ignite economic growth. 

The stream engine, internal combustion engine, materials science, electricity, the computer and the internet are prior examples of GPTs. Biotechnology and nanotechnology are other possible GPTs, but are not yet widely acknowledged to have already done so. 

Most of us likely believe AI is going to be added to that list. Buckle up.

What is an "AI Appliance"?

As we move into the AI era of devices and appliances, it seems inevitable that some will seek to redefine devices as “AI appliances,” even if most firms will instead seek only to develop AI apps that run on standard appliances (phones, PCs, sensors). 

Such AI appliances might feature personalization, predictive maintenance, contextual awareness, continuous learning, proactive assistance or enhanced security. 

AI-powered PCs could be designed to support on-the-device machine learning and natural language processing or provide augmented reality experiences. 

AI appliances likely will be able to learn about their users' preferences and habits, and tailor their operation accordingly.

AI appliances will be able to monitor their own performance and predict when they are likely to need maintenance. Also, AI appliances will be able to anticipate their users' needs and provide assistance without being asked.

Enhanced security: AI appliances will be able to detect and prevent security breaches.

Here are some specific examples of AI appliances that are already being developed:

Software Applications wants to develop a desktop PC operating system optimized for generative artificial intelligence. The effort is early so it is hard to say much about what they might develop. 

An example the firm cites is that “sometimes you’ve got a browser window open with a schedule on it, and you just want to say, ‘add this to my calendar,’ and somehow, there’s no way to do that.” An AI PC would be able to do so. 

Most other startups such as Rewind AI,  are building personalized AI systems for the desktop. Rewind AI seems focused on the function of note taking on Mac and iOS devices. 

Moveworks develops automated IT support solutions that use AI to monitor and troubleshoot IT systems, identify and resolve issues, and provide proactive support to users.

Coactive AI uses AI to automate the process of retrieving and using visual data. 

Midjourney develops chatbot applications that use AI to generate images.

DeepL provides a machine translation service. 

Frame AI: Offers a platform for building and deploying AI models on embedded devices, such as smartphones and smart home appliances.

Uizard features a no-code AI platform that allows users to create AI applications without any programming experience.

Sherpa provides a virtual personal assistant.

BigPanda provides an AIOps capability that helps IT teams resolve IT outages and incidents more quickly and effectively.

CognitiveScale develops AI-powered customer service solutions for various industries, including healthcare, insurance, financial services, and digital commerce.